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James Sharpnack

James L. Sharpnack

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Person information

affiliation: University of California, Davis
affiliation (former): University of California, San Diego, Department of Mathematics
affiliation (former): Carnegie Mellon University, Machine Learning Department

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Books and Theses

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2013
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James Sharpnack:
Graph Structured Normal Means Inference. Carnegie Mellon University, USA, 2013

Journal Articles

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2023
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James Sharpnack:
On L²-Consistency of Nearest Neighbor Matching. IEEE Trans. Inf. Theory 69(6): 3978-3988 (2023)
2017
[j3]
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Oscar Hernan Madrid Padilla, James Sharpnack, James G. Scott, Ryan J. Tibshirani:
The DFS Fused Lasso: Linear-Time Denoising over General Graphs. J. Mach. Learn. Res. 18: 176:1-176:36 (2017)
2016
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Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani:
Trend Filtering on Graphs. J. Mach. Learn. Res. 17: 105:1-105:41 (2016)
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James Sharpnack, Alessandro Rinaldo, Aarti Singh:
Detecting Anomalous Activity on Networks With the Graph Fourier Scan Statistic. IEEE Trans. Signal Process. 64(2): 364-379 (2016)

Conference and Workshop Papers

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2023
[c25]
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Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton:
RLSbench: Domain Adaptation Under Relaxed Label Shift. ICML 2023: 10879-10928
2022
[c24]
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Qin Ding, Cho-Jui Hsieh, James Sharpnack:
Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks. AISTATS 2022: 7111-7123
[c23]
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Stephen Sheng, Keerthi Vasan G. C, Chi Po P. Choi, James Sharpnack, Tucker Jones:
An Unsupervised Hunt for Gravitational Lenses. AISTATS 2022: 9827-9843
[c22]
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Nick Erickson, Xingjian Shi, James Sharpnack, Alexander J. Smola:
Multimodal AutoML for Image, Text and Tabular Data. KDD 2022: 4786-4787
[c21]
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Qin Ding, Yue Kang, Yi-Wei Liu, Thomas Chun Man Lee, Cho-Jui Hsieh, James Sharpnack:
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. NeurIPS 2022
2021
[c20]
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Qin Ding, Cho-Jui Hsieh, James Sharpnack:
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling. AISTATS 2021: 1585-1593
2020
[c19]
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Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh:
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. AISTATS 2020: 776-787
[c18]
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Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack:
SSE-PT: Sequential Recommendation Via Personalized Transformer. RecSys 2020: 328-337
2019
[c17]
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Kirill Paramonov, Dmitry Shemetov, James Sharpnack:
Estimating Graphlet Statistics via Lifting. KDD 2019: 587-595
[c16]
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Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James L. Sharpnack:
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers. NeurIPS 2019: 24-34
2018
[c15]
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James Sharpnack:
Learning Patterns for Detection with Multiscale Scan Statistics. COLT 2018: 950-969
[c14]
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Liwei Wu, Cho-Jui Hsieh, James Sharpnack:
SQL-Rank: A Listwise Approach to Collaborative Ranking. ICML 2018: 5311-5320
2017
[c13]
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Liwei Wu, Cho-Jui Hsieh, James Sharpnack:
Large-scale Collaborative Ranking in Near-Linear Time. KDD 2017: 515-524
[c12]
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Veeranjaneyulu Sadhanala, Yu-Xiang Wang, James Sharpnack, Ryan J. Tibshirani:
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods. NIPS 2017: 5800-5810
[c11]
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Kevin Lin, James Sharpnack, Alessandro Rinaldo, Ryan J. Tibshirani:
A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening. NIPS 2017: 6884-6893
2015
[c10]
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Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani:
Trend Filtering on Graphs. AISTATS 2015
2013
[c9]
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Akshay Krishnamurthy, James Sharpnack, Aarti Singh:
Recovering graph-structured activations using adaptive compressive measurements. ACSSC 2013: 765-769
[c8]
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James Sharpnack, Aarti Singh, Akshay Krishnamurthy:
Detecting Activations over Graphs using Spanning Tree Wavelet Bases. AISTATS 2013: 536-544
[c7]
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James Sharpnack, Aarti Singh, Alessandro Rinaldo:
Changepoint Detection over Graphs with the Spectral Scan Statistic. AISTATS 2013: 545-553
[c6]
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James Sharpnack:
A path algorithm for localizing anomalous activity in graphs. GlobalSIP 2013: 341-344
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James Sharpnack, Aarti Singh:
Near-optimal and computationally efficient detectors for weak and sparse graph-structured patterns. GlobalSIP 2013: 443-446
[c4]
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James Sharpnack, Akshay Krishnamurthy, Aarti Singh:
Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic. NIPS 2013: 1959-1967
2012
[c3]
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Mladen Kolar, James Sharpnack:
Variance Function Estimation in High-dimensions. ICML 2012
[c2]
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James Sharpnack, Aarti Singh, Alessandro Rinaldo:
Sparsistency of the Edge Lasso over Graphs. AISTATS 2012: 1028-1036
2010
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James Sharpnack, Aarti Singh:
Identifying graph-structured activation patterns in networks. NIPS 2010: 2137-2145

Informal and Other Publications

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2023
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Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary C. Lipton:
RLSbench: Domain Adaptation Under Relaxed Label Shift. CoRR abs/2302.03020 (2023)
2021
[i15]
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  - journals/corr/abs-2106-02978
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Qin Ding, Cho-Jui Hsieh, James Sharpnack:
Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks. CoRR abs/2106.02978 (2021)
[i14]
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  - journals/corr/abs-2106-02979
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Qin Ding, Yi-Wei Liu, Cho-Jui Hsieh, James Sharpnack:
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. CoRR abs/2106.02979 (2021)
2020
[i13]
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  - journals/corr/abs-2002-05289
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Qin Ding, Cho-Jui Hsieh, James Sharpnack:
Multiscale Non-stationary Stochastic Bandits. CoRR abs/2002.05289 (2020)
[i12]
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  - journals/corr/abs-2006-04012
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Qin Ding, Cho-Jui Hsieh, James Sharpnack:
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling. CoRR abs/2006.04012 (2020)
2019
[i11]
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  - journals/corr/abs-1905-10630
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Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack:
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers. CoRR abs/1905.10630 (2019)
[i10]
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  - journals/corr/abs-1905-12217
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Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh:
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. CoRR abs/1905.12217 (2019)
[i9]
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  - journals/corr/abs-1908-05435
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Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack:
Temporal Collaborative Ranking Via Personalized Transformer. CoRR abs/1908.05435 (2019)
[i8]
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  - journals/corr/abs-1911-09228
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Weitang Liu, Lifeng Wei, James Sharpnack, John D. Owens:
Unsupervised Object Segmentation with Explicit Localization Module. CoRR abs/1911.09228 (2019)
2018
[i7]
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  - journals/corr/abs-1802-06054
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James Sharpnack:
Learning Patterns for Detection with Multiscale Scan Statistics. CoRR abs/1802.06054 (2018)
[i6]
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  - journals/corr/abs-1803-00114
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Liwei Wu, Cho-Jui Hsieh, James Sharpnack:
SQL-Rank: A Listwise Approach to Collaborative Ranking. CoRR abs/1803.00114 (2018)
[i5]
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  - journals/corr/abs-1805-09978
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Shitong Wei, Oscar Hernan Madrid Padilla, James Sharpnack:
Distributed Cartesian Power Graph Segmentation for Graphon Estimation. CoRR abs/1805.09978 (2018)
2014
[i4]
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Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani:
Trend Filtering on Graphs. CoRR abs/1410.7690 (2014)
2013
[i3]
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  - journals/corr/abs-1305-0213
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Akshay Krishnamurthy, James Sharpnack, Aarti Singh:
Recovering Graph-Structured Activations using Adaptive Compressive Measurements. CoRR abs/1305.0213 (2013)
2012
[i2]
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  - journals/corr/abs-1206-0773
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James Sharpnack, Alessandro Rinaldo, Aarti Singh:
Changepoint Detection over Graphs with the Spectral Scan Statistic. CoRR abs/1206.0773 (2012)
[i1]
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  - journals/corr/abs-1206-0937
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Akshay Krishnamurthy, James Sharpnack, Aarti Singh:
Detecting Activations over Graphs using Spanning Tree Wavelet Bases. CoRR abs/1206.0937 (2012)

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